Titlebook: Affective Information Processing; Jianhua Tao,Tieniu Tan Book 2009 Springer-Verlag London 2009 Affect.Affective Computing.Affective Inform

爆裂

書目名稱Affective Information Processing影響因子(影響力)




書目名稱Affective Information Processing影響因子(影響力)學(xué)科排名




書目名稱Affective Information Processing網(wǎng)絡(luò)公開度




書目名稱Affective Information Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Affective Information Processing被引頻次




書目名稱Affective Information Processing被引頻次學(xué)科排名




書目名稱Affective Information Processing年度引用




書目名稱Affective Information Processing年度引用學(xué)科排名




書目名稱Affective Information Processing讀者反饋




書目名稱Affective Information Processing讀者反饋學(xué)科排名

過剩

Affect and Emotions in Intelligent Agents: Why and How?fit between an organism‘s functioning and the demands and opportunities that are presented by the environment in which it finds itself. It is proposed that effective functioning requires the interplay of four elements—affect, cognition, motivation, and behavior—and that the level of information proc

SPALL

Cognitive Emotion Modeling in Natural Language Communicationignificant projects in this domain in recent years. The review is focused on probabilistic dynamic models, due to the key role of uncertainty in the relationships among the variables involved: the authors‘ experience in this domain is discussed by outlining open problems. Two aspects are discussed i

configuration

ARENA

Affective Agents for Education Against Bullyingstem is discussed and the chapter considers issues relating to believability. It describes the emotionally driven architecture used for characters as well as the management of the overall story and finally considers issues relating to evaluation of systems like this.

凌辱

Emotion Perception and Recognition from Speechs more and more important. This chapter begins by introducing the correlations be?tween basic speech features such as pitch, intensity, formants, MFCC, and so on, and the emotions. Several recognition methods are then described to illustrate the performance of the previously proposed models, includi

積習(xí)已深

intimate

Emotional Speech Generation by Using Statistic Prosody Conversion Methodsression Tree (CART) model. Unlike the rule-based or linear modification method, the GMM and CART models try to map the subtle prosody distributions between neutral and emotional speech. A pitch target model that is optimized to describe Mandarin F0 contours is also introduced. For all conversion met

TSH582

大門在匯總

Automatic Facial Action Unit Recognition by Modeling Their Semantic And Dynamic Relationshipstion unit (AU) recognition approaches often recognize AUs or certain AU combinations in dividually and statically, ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently due to the richness, ambi